This server has two tools with critically incomplete definitions. Both tools have descriptions under 20 characters (add_chunks: 'added chunks to memory.mp4', search: 'Semantic search over memory video chunks', first is only 29 chars but lacks action context, second is 38 chars but generic). Input schemas are visible but lack critical context: 'chunks' parameter has no description in the schema definition visible in source, and 'top_k' has a generic description. Critically, there are NO output schemas documented anywhere, the tools return plain strings ('"added chunks to memory.mp4"' and '"\n".join(res_strs)') which are unstructured and provide no guidance to LLMs about what data to extract or how to chain with other tools. The 'add_chunks' tool is vaguely named, it doesn't signal that it modifies state or what the chunks contain semantically. No error handling, no recovery guidance, no output structure. Tool descriptions fail to explain WHEN to use each tool, WHAT they return, or HOW they depend on each other (both operate on the same 'memory.mp4' / 'memory_index.json' state, suggesting coupling that's not documented). This is typical poor-quality community tooling.

• Expand tool descriptions to 100 - 200 chars. Example for 'add_chunks': 'Appends text chunks to the memory video and rebuilds the video index for semantic search. Chunks are embedded and added to memory.mp4. Call this to add new information before searching.'
• Document output schemas explicitly. E.g., add_chunks should return {"success": true, "count_added": 5, "video_path": "memory.mp4"} instead of a plain string. search should return {"results": [{"chunk_id": "...", "text": "...", "relevance_score": 0.95}], "total_results": 12}.
• Rename 'add_chunks' to a more specific verb: 'append_to_memory_video' or 'index_text_chunks' to make the action and side effects clear.
• Add input constraints: 'chunks' should have minItems (≥1), maxItems (e.g., ≤1000), and per-item max length. 'top_k' should specify valid range (1 - 100) and explain the tradeoff (higher = slower, more results).
• Add error handling: wrap encoder.add_chunks() and retriever.search() in try-except, catch file-not-found, index corruption, embedding failures, and return structured error responses: {"success": false, "error": "Index file not found", "recovery": "Call add_chunks first to initialize the video."}
• Document prerequisites: add tool note 'Requires video file memory.mp4 and index memory_index.json to exist. Call add_chunks to initialize.' Alternatively, refactor to auto-initialize on first call.
• Add composition guidance: 'search depends on prior add_chunks calls. If search returns no results, verify chunks were added and the index was rebuilt.' This prevents agent confusion.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry